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The dataset generation failed because of a cast error
Error code:   DatasetGenerationCastError
Exception:    DatasetGenerationCastError
Message:      An error occurred while generating the dataset

All the data files must have the same columns, but at some point there are 10 new columns ({'overs', 'opposition', 'economy', 'conceded', 'wides', 'noballs', 'dots', 'wickets', 'maidens', 'bowler id'}) and 7 missing columns ({'batsman', 'bowler', 'fielders', 'strikeRate', 'runs', 'wicketType', 'isOut'}).

This happened while the csv dataset builder was generating data using

hf://datasets/bhuvaneshprasad/test-cricket-dataset-1877-2014/test_Bowling_Card.csv (at revision d63e838c0d537afb843bd7e96f628bb175846696)

Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
                  writer.write_table(table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              Match ID: int64
              innings: int64
              team: string
              opposition: string
              bowler id: int64
              overs: double
              balls: int64
              maidens: int64
              conceded: int64
              wickets: int64
              economy: double
              dots: double
              fours: double
              sixes: double
              wides: int64
              noballs: int64
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2047
              to
              {'Match ID': Value(dtype='int64', id=None), 'innings': Value(dtype='int64', id=None), 'team': Value(dtype='string', id=None), 'batsman': Value(dtype='int64', id=None), 'runs': Value(dtype='float64', id=None), 'balls': Value(dtype='float64', id=None), 'fours': Value(dtype='float64', id=None), 'sixes': Value(dtype='float64', id=None), 'strikeRate': Value(dtype='float64', id=None), 'isOut': Value(dtype='bool', id=None), 'wicketType': Value(dtype='string', id=None), 'fielders': Value(dtype='string', id=None), 'bowler': Value(dtype='float64', id=None)}
              because column names don't match
              
              During handling of the above exception, another exception occurred:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1321, in compute_config_parquet_and_info_response
                  parquet_operations = convert_to_parquet(builder)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 935, in convert_to_parquet
                  builder.download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
                  self._download_and_prepare(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single
                  raise DatasetGenerationCastError.from_cast_error(
              datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
              
              All the data files must have the same columns, but at some point there are 10 new columns ({'overs', 'opposition', 'economy', 'conceded', 'wides', 'noballs', 'dots', 'wickets', 'maidens', 'bowler id'}) and 7 missing columns ({'batsman', 'bowler', 'fielders', 'strikeRate', 'runs', 'wicketType', 'isOut'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/bhuvaneshprasad/test-cricket-dataset-1877-2014/test_Bowling_Card.csv (at revision d63e838c0d537afb843bd7e96f628bb175846696)
              
              Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)

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Match ID
int64
innings
int64
team
string
batsman
int64
runs
float64
balls
float64
fours
float64
sixes
float64
strikeRate
float64
isOut
bool
wicketType
string
fielders
string
bowler
float64
1,213,062
1
Bangladesh
48,391
3
5
0
0
60
true
lbw
null
59,220
1,213,062
1
Bangladesh
80,555
0
2
0
0
0
true
caught
['53493']
95,855
1,213,062
1
Bangladesh
70,872
44
110
6
0
40
true
caught
['54018']
59,220
1,213,062
1
Bangladesh
58,225
30
59
5
0
50.84
true
caught
['54018']
95,855
1,213,062
1
Bangladesh
47,352
25
48
4
0
52.08
true
caught
['53493']
95,855
1,213,062
1
Bangladesh
50,414
63
140
7
1
45
true
caught
['54018']
103,399
1,213,062
1
Bangladesh
66,691
33
46
7
0
71.73
true
lbw
null
53,639
1,198,242
1
Pakistan
49,236
1
5
0
0
20
true
lbw
null
10,829
1,213,062
1
Bangladesh
59,679
24
72
4
0
33.33
true
caught
['45170']
53,639
1,198,242
1
Pakistan
48,306
60
111
7
0
54.05
true
caught
['59611']
72,103
1,213,062
1
Bangladesh
52,364
1
9
0
0
11.11
true
bowled
null
95,855
1,213,062
1
Bangladesh
60,029
0
5
0
0
0
true
run out
['59220']
null
1,198,242
1
Pakistan
11,475
20
85
1
0
23.52
true
caught
['59611']
10,829
1,214,666
1
Zimbabwe
49,118
64
152
9
0
42.1
true
caught
['86601']
86,601
1,213,062
1
Bangladesh
86,321
0
4
0
0
0
false
not out
['-']
null
1,212,542
1
Zimbabwe
49,274
null
null
null
null
null
false
DNB
null
null
1,198,242
1
Pakistan
56,880
47
127
3
0
37
true
caught
['53271']
48,440
1,214,666
1
Zimbabwe
62,298
2
24
0
0
8.33
true
caught
['86601']
60,029
1,213,062
2
Pakistan
49,236
100
160
11
0
62.5
true
bowled
null
59,679
1,212,542
1
Zimbabwe
49,118
9
44
1
0
20.45
true
caught
['61131']
78,235
1,198,242
1
Pakistan
53,493
5
13
1
0
38.46
true
caught
['65480']
48,440
1,214,666
1
Zimbabwe
47,205
107
227
13
0
47.13
true
bowled
null
86,601
1,213,062
2
Pakistan
48,306
0
6
0
0
0
true
caught
['66691']
60,029
1,198,242
1
Pakistan
47,099
0
4
0
0
0
true
lbw
null
49,496
1,212,542
1
Zimbabwe
62,298
38
97
4
0
39.17
true
bowled
null
46,995
1,198,242
1
Pakistan
54,018
72
139
7
0
51.79
true
caught
['72167']
48,440
1,212,542
1
Zimbabwe
47,205
12
11
1
1
109.09
true
caught
['57982']
62,760
1,213,062
2
Pakistan
11,475
34
59
4
0
57.62
true
caught
['70872']
60,029
1,214,666
1
Zimbabwe
45,253
10
11
1
0
90.9
true
bowled
null
86,601
1,198,242
1
Pakistan
45,170
5
16
1
0
31.25
true
caught
['53271']
10,829
1,212,542
1
Zimbabwe
45,253
62
62
10
1
100
true
lbw
null
46,995
1,183,534
1
Australia
48,739
45
80
3
0
56.25
true
caught
['47231']
49,219
1,237,356
1
Sri Lanka
48,988
22
20
4
0
110
true
bowled
null
66,941
1,213,062
2
Pakistan
56,880
143
193
18
1
74.09
true
caught
['50414']
60,029
1,198,241
1
Pakistan
49,236
156
319
18
2
48.9
true
lbw
null
48,440
1,214,666
1
Zimbabwe
52,319
18
62
3
0
29.03
true
caught
['66691']
86,601
1,225,247
1
England
59,611
30
85
4
0
35.29
true
lbw
null
61,982
1,198,242
1
Pakistan
95,855
0
19
0
0
0
true
run out
['65480']
null
1,233,958
1
New Zealand
59,148
27
53
4
0
50.94
true
caught
['104283']
84,179
1,198,243
1
England
59,611
6
13
1
0
46.15
true
caught
['49236']
95,855
1,212,542
1
Zimbabwe
47,206
107
137
10
3
78.1
true
bowled
null
62,760
1,183,534
1
Australia
54,337
18
39
3
0
46.15
true
caught
['44930']
47,231
1,237,356
1
Sri Lanka
52,373
16
29
2
0
55.17
true
caught
['58406']
74,351
1,213,062
2
Pakistan
53,493
65
129
9
0
50.38
true
caught
['66691']
86,321
1,198,241
1
Pakistan
48,306
16
37
2
0
43.24
true
bowled
null
72,379
1,214,666
1
Zimbabwe
49,274
7
35
1
0
20
true
lbw
null
60,029
1,225,247
1
England
65,480
0
4
0
0
0
true
bowled
null
61,982
1,198,242
1
Pakistan
59,220
2
20
0
0
10
true
lbw
null
48,440
1,233,958
1
New Zealand
61,839
14
19
2
0
73.68
true
bowled
null
61,982
1,198,243
1
England
65,480
22
47
1
0
46.8
true
lbw
null
45,170
1,212,542
1
Zimbabwe
52,319
72
99
4
2
72.72
true
caught
['47023']
81,061
1,183,534
1
Australia
78,285
215
363
19
1
59.22
true
caught
['48641']
48,641
1,237,356
1
Sri Lanka
70,888
12
16
2
0
75
true
caught
['66941']
63,651
1,213,062
2
Pakistan
53,639
75
103
7
2
72.81
true
caught
['48391']
59,679
1,198,241
1
Pakistan
11,475
0
6
0
0
0
true
lbw
null
49,496
1,214,666
1
Zimbabwe
51,554
30
74
3
0
40.54
true
caught
['86601']
59,679
1,225,247
1
England
46,925
18
58
4
0
31.03
true
bowled
null
61,982
1,198,242
1
Pakistan
103,399
1
10
0
0
10
false
not out
['-']
null
1,233,958
1
New Zealand
67,178
43
87
4
0
49.42
true
caught
['59339']
61,982
1,198,243
1
England
72,167
267
393
34
1
67.93
true
stumping
['54018']
53,493
1,212,542
1
Zimbabwe
51,554
31
69
3
0
44.92
true
caught
['61131']
81,061
1,183,534
1
Australia
50,281
63
182
4
0
34.61
true
caught
['44930']
47,231
1,237,356
1
Sri Lanka
52,371
85
161
11
0
52.79
true
caught
['46933']
74,351
1,213,062
2
Pakistan
54,018
10
23
1
0
43.47
true
caught
['47352']
52,364
1,198,241
1
Pakistan
56,880
69
106
11
0
65.09
true
caught
['52656']
10,829
1,214,666
1
Zimbabwe
59,384
8
31
2
0
25.8
true
caught
['66691']
60,029
1,225,247
1
England
72,167
10
26
2
0
38.46
true
lbw
null
59,339
1,198,242
2
England
59,611
0
4
0
0
0
true
caught
['53493']
95,855
1,233,958
1
New Zealand
44,930
9
12
1
0
75
true
caught
['104283']
61,982
1,198,243
1
England
52,656
29
51
3
0
56.86
true
caught
['54018']
103,399
1,212,542
1
Zimbabwe
55,145
33
99
4
0
33.33
true
lbw
null
62,760
1,183,534
1
Australia
49,024
22
32
2
1
68.75
true
bowled
null
48,432
1,237,356
1
Sri Lanka
62,760
79
106
11
1
74.52
false
retired not out
['-']
null
1,213,062
2
Pakistan
45,170
5
21
1
0
23.8
true
lbw
null
52,364
1,198,241
1
Pakistan
53,493
7
22
1
0
31.81
true
caught
['53320']
48,440
1,214,666
1
Zimbabwe
69,959
0
6
0
0
0
true
lbw
null
60,029
1,225,247
1
England
53,320
43
97
7
0
44.32
true
caught
['61416']
59,339
1,198,242
2
England
65,480
32
95
3
0
33.68
true
caught
['54018']
59,220
1,233,958
1
New Zealand
66,842
174
280
21
1
62.14
true
caught
['56801']
59,349
1,198,243
1
England
83,357
3
15
0
0
20
true
bowled
null
45,170
1,212,542
1
Zimbabwe
59,384
13
47
1
0
27.65
true
caught
['46995']
81,061
1,183,534
1
Australia
66,190
10
42
1
0
23.8
true
caught
['47492']
64,947
1,237,356
1
Sri Lanka
61,131
49
86
6
0
56.97
true
lbw
null
74,351
1,213,062
2
Pakistan
95,855
3
12
0
0
25
true
lbw
null
52,364
1,198,241
1
Pakistan
54,018
9
41
0
0
21.95
true
caught
['53271']
49,496
1,214,666
1
Zimbabwe
89,127
0
4
0
0
0
true
lbw
null
59,679
1,225,247
1
England
83,357
12
13
2
0
92.3
true
caught
['61416']
59,339
1,198,242
2
England
72,167
53
99
7
0
53.53
true
lbw
null
59,220
1,233,958
1
New Zealand
47,492
30
51
6
0
58.82
true
bowled
null
72,397
1,198,243
1
England
53,271
152
311
13
2
48.87
true
caught
['47099']
47,099
1,212,542
1
Zimbabwe
72,441
11
19
2
0
57.89
false
not out
['-']
null
1,183,534
1
Australia
34,747
35
92
3
0
38.04
true
bowled
null
47,231
1,237,356
1
Sri Lanka
61,690
66
87
3
5
75.86
false
not out
['-']
null
1,213,062
2
Pakistan
59,220
1
26
0
0
3.84
false
not out
['-']
null
1,198,241
1
Pakistan
84,937
45
76
3
0
59.21
true
caught
['52656']
71,499
1,214,666
1
Zimbabwe
62,301
6
13
1
0
46.15
false
not out
['-']
null
1,225,247
1
England
53,271
35
47
6
0
74.46
true
caught
['61416']
59,339
1,198,242
2
England
52,656
9
35
0
0
25.71
false
not out
['-']
null
1,233,958
1
New Zealand
58,772
42
68
5
0
61.76
true
lbw
null
84,179
1,198,243
1
England
49,496
40
54
5
0
74.07
true
caught
['45170']
47,099
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